Radiography refers to a general system, or modality, for recording a radiation image from the transmission of x-rays through an object, such as a body of a patient. Conventional radiography uses a film/screen combination as the capture device, while digital radiography can employ a digital detector (DR) or a stimulable phosphor plate (generally referred to as computed radiography, CR). For either digital radiography technology, the output digital signal is usually converted into a unit that is linear with the logarithm of incident exposure. Digital systems can record radiation exposure over a wide dynamic range, typically on the order of 10,000:1, so that exposure error is seldom a problem.
As with conventional radiography, equipment acceptance and continued quality assurance are required for digital radiography systems, to varying degrees, for each diagnostic institution and/or region.
For example, guidelines for acceptance and scheduled testing of mammography systems have been outlined in the European Protocol for the Quality Control of the Physical and Technical Aspects of Mammography Screening, Part B: Digital Mammography, also generally referred to as EPQCM. Refer to R. van Engen, K. Young, H. Bosmans, and M. Thijssen, European Protocol for the Quality Control of the Physical and Technical Aspects of Mammography Screening, Part B: Digital Mammography, Draft Edition January 2005, European Commission, National Expert and Training Centre for Breast Cancer Screening 451, University Medical Centre Nijmegen, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands Nijmegan, The Netherlands, January 2005.
One image quality criterion prescribed by the EPQCM addresses the requirement that low-contrast small-diameter objects be visibly differentiated from a uniform background. This stands as a surrogate for the requirement for diagnostic systems to provide adequate visibility of masses and micro-calcifications. Contrast-detail studies have traditionally been used for this purpose. See for example, A. Rose, Vision Human and Electronic, Plenum Press, New York (1973); M. Thijssen et al., “A definition of image quality: the image quality figure,” BIR Report 20, pp 29-34 (1990); S. R. Thompson and K. Faulkner, “A phantom for the measurement of contrast detail performance in film-screen mammography,” British J. Radiol. 64, 1049-1055 (1991); L-N. D. Loo, K. Doi, M. Ishida, C. E. Metz, “An empirical investigation of variability in contrast-detail diagram measurements,” Proc SPIE 419, 68-76 (1983); G. Cohen, D. L. McDaniel and L. K. Wagner, “Analysis of variations in contrast-detail experiments,” Med. Phys. 11, 469-473 (1984); and T. Fearon et al. “A comparison evaluation of rare-earth screen-film systems: system speed, contrast, sensitometry, RMS noise, square-wave response function and contrast-dose-detail analysis,” Invest. Radiol. 21, 654-662 (1986).
The EPQCM recognizes the well-known limitations of traditional contrast-detail methods, based on a single image of a Rose-Burger phantom, by adopting multiple images of an alternative forced-choice phantom. (See R. F. Wagner, C. E. Metz and D. G. Brown, “Signal detection theory and medical image assessment,” in Recent developments in digital imaging, ed. K. Doi, L. Lanzl and P-J. P. Lin, AAPM Monograph 12, American Institute of Physics (1985).) This choice is supported by a recent comparison of subjective and objective measures of detail detectability as well as detailed analysis of the efficiency of multiple-forced-choice methods. Refer to M. J. Tapiovaara and M. Sanborg, “How should low-contrast detectibility be measured in fluoroscopy,” Med. Phys. 31, 2564-2576(2004). Refer also to A. E. Burgess, “Comparison of receiver operating characteristic and forced choice observer performance measurement methods,” Med. Phys. 22, 643-655 (1995).
The EPQCM methodology is described in detail in section 2.4.1 (threshold contrast sensitivity) of the EPQCM. In particular, images of a suitable contrast-detail phantom are to be acquired with clinical technique factors. Visual scoring and analysis predicts the threshold contrast target for each target diameter.
The CDMAM phantom template employs a plurality of squares, wherein each square contains two identical discs (same thickness, same diameter), one in the center and one in a randomly chosen corner.
With the CDMAM phantom (i.e., contrast-detail phantom for mammography images), the threshold contrast of an imaging system is determined as a function of object diameter by the detection of pairs of low-contrast objects. The most recent version of the phantom, CDMAM 3.4, tests the ability of observers to visualize gold disks ranging in diameter from about 0.06 to about 2.0 mm and in thickness from about 0.03 to about 2.0 um. Refer to R. Visser and N. Karssemeijer, “CDCOM Manual: software for automated readout of CDMAM 3.4 images”. Note that the CDCOM software, manual and sample images are posted at http:www.euref.org.
This results in an approximate radiation contrast range of about 0.5% to about 30%. K. R. Bijkerk, M. A. O. See Thijssen, Th. J. M. Arnoldussen, IWDM 2000 report: Modification of the CDMAM contrast-detail phantom for image quality of Full Field Digital Mammography systems, University Medical Centre Nijmegan, St. Radboud, The Netherlands, 2000. The contrast range is approximate, which is due to the clinical variability of the technique (filtration, kVp, and detector material) used for testing. The CDMAM 3.4 phantom was redesigned from older versions specifically to accommodate digital systems that potentially have improved-system DQE and MTF over traditional film screen systems. See M. A. O. Thijssen, W. Veldkamp, R. Van Engen, M. Swinkels, N. Karssemeijer, J. Hendricks, “Comparison of the detectability of small details in a film-screen and a digital mammography system by the imaging of a new CDMAM-phantom”, Proceedings of IWDM 2000, pp. 666-672, M. Yaffe ed, Medical Physics Publishing, Madison, Wis., Toronto, 2000.
Although not permitted by the EPQCM guidelines, automated software observers have been developed to evaluate CDMAM images. One of these was developed by Karssemeijer and Thijssen. Refer to N. Karssemeijer, M. A. O. Thijssen, “Determination of contrast-detail curves of mammography systems by automated image analysis”in Digital Mammography '96. Proceedings of the 3rd International Workshop on Digital Mammography, 155-160 (1996). It is believed to be available on the EUREF website (http:www.euref.org) along with a manual.
Other automated scoring methods continue to be developed in recognition of the complexities associated with implementing the visual threshold contrast sensitivity test. For example, Rico et al. implemented a software scoring method that they compared with visual measurements as a function of dose. (See R. Rico, S. Muller, G. Peter, A. Noël, and J. Stines, “Automatic scoring of CDMAM: A dose study,” Proc. SPIE 5034, 164-173 (2003).) Although a good correlation of IQF (a summary performance measure) was reported, the software method demonstrated higher detection sensitivity than that of the human observers in the study. The use of the IQF metric precludes analysis of their data in terms of the EPQCM criteria.
Other analytical approaches are being investigated and may be promising. Ongoing work in IEC working group 62B is working to standardize the measurement of mammographic DQE in a manner similar to the current standard for general radiography. (See: “Medical electrical equipment—Characteristics of digital X-ray imaging devices—Part 1: Determination of the detective quantum efficiency” IEC 62220-1 Ed. 1, International Electrotechnical Commission (2003).) Such measurements can be used together with well-established methods to predict signal-to-noise performance metrics for either ideal or human observers. (See P. Sharp et al. “Medical imaging—the assessment of image quality,” ICRU Report 54, International Commission on Radiation Unit, Bethesda, Md. (1995).)
Work is also currently underway in several laboratories to produce a software scoring tool that matches human visual performance.
At present, the EPQCM is being used as a guideline and is not used as a regulatory document. It is, however, anticipated that region specific regulations may be implemented based on the guidance of the EPQCM. Therefore, some clinical sites are beginning to require compliance with the EPQCM guidelines for equipment-purchase tenders.
Therefore, there exists a need for a tool to aid in the cumbersome and time-consuming image quality test, without compromising the requirement for human observers to complete the test.
The present invention is directed to a method to aid in the image quality test, without compromising the requirement for human observers to complete the test.